scholarly journals Practical Implementation of Lattice QCD Simulation on Intel Xeon Phi Knights Landing

Author(s):  
Issaku Kanamori ◽  
Hideo Matsufuru
2018 ◽  
Vol 175 ◽  
pp. 02009
Author(s):  
Carleton DeTar ◽  
Steven Gottlieb ◽  
Ruizi Li ◽  
Doug Toussaint

With recent developments in parallel supercomputing architecture, many core, multi-core, and GPU processors are now commonplace, resulting in more levels of parallelism, memory hierarchy, and programming complexity. It has been necessary to adapt the MILC code to these new processors starting with NVIDIA GPUs, and more recently, the Intel Xeon Phi processors. We report on our efforts to port and optimize our code for the Intel Knights Landing architecture. We consider performance of the MILC code with MPI and OpenMP, and optimizations with QOPQDP and QPhiX. For the latter approach, we concentrate on the staggered conjugate gradient and gauge force. We also consider performance on recent NVIDIA GPUs using the QUDA library.


Author(s):  
Josh Tobin ◽  
Alexander Breuer ◽  
Alexander Heinecke ◽  
Charles Yount ◽  
Yifeng Cui

2016 ◽  
Author(s):  
Hirokazu Kobayashi ◽  
Yoshifumi Nakamura ◽  
Shinji Takeda ◽  
Yoshinobu Kuramashi

2018 ◽  
Vol 175 ◽  
pp. 02007 ◽  
Author(s):  
Peter Georg ◽  
Daniel Richtmann ◽  
Tilo Wettig

We describe our experience porting the Regensburg implementation of the DD-αAMG solver from QPACE 2 to QPACE 3. We first review how the code was ported from the first generation Intel Xeon Phi processor (Knights Corner) to its successor (Knights Landing). We then describe the modifications in the communication library necessitated by the switch from InfiniBand to Omni-Path. Finally, we present the performance of the code on a single processor as well as the scaling on many nodes, where in both cases the speedup factor is close to the theoretical expectations.


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